Do basic validation and transform object to a "standardized" list containing models, and their properties such as x, y, whether it is a (multinomial) clasification or not etc.
Do basic validation and transform object to a "standardized" list containing models, and
their properties such as x, y, whether it is a (multinomial) clasification or not etc.
.process_models_or_automl( object, newdata, require_single_model = FALSE, require_multiple_models = FALSE, top_n_from_AutoML = NA, only_with_varimp = FALSE, best_of_family = FALSE, require_newdata = TRUE )
object |
Can be a single model/model_id, vector of model_id, list of models, H2OAutoML object |
newdata |
An H2OFrame with the same format as training frame |
require_single_model |
If true, make sure we were provided only one model |
require_multiple_models |
If true, make sure we were provided at least two models |
top_n_from_AutoML |
If set, don't return more than top_n models (applies only for AutoML object) |
only_with_varimp |
If TRUE, return only models that have variable importance |
best_of_family |
If TRUE, return only the best of family models; if FALSE return all models in |
require_newdata |
If TRUE, require newdata to be specified; otherwise allow NULL instead, this can be used when there is no need to know if the problem is (multinomial) classification. |
a list with the following names leader, is_automl, models,
is_classification, is_multinomial_classification, x, y, model
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